





'''simple docstring'''

import unittest

import numpy as np

from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
			import torch

if is_pytesseract_available():
			from PIL import Image

			from transformers import LayoutLMvaImageProcessor

class    UpperCAmelCase			(    unittest.TestCase	):




		def __init__(self   :						Union[str, Any]				,      A__   :						Union[str, Any]				,      A__   :						List[Any]=7				,      A__   :						List[Any]=3				,      A__   :						List[str]=1_8				,      A__   :						Optional[int]=3_0				,      A__   :						List[Any]=4_0_0				,      A__   :						str=True				,      A__   :						List[str]=None				,      A__   :						Optional[Any]=True				,      )       ->			Union[str, Any]:
						lowercase    =			size if size is not None else {"height": 1_8, "width": 1_8}
						lowercase    =			parent
						lowercase    =			batch_size
						lowercase    =			num_channels
						lowercase    =			image_size
						lowercase    =			min_resolution
						lowercase    =			max_resolution
						lowercase    =			do_resize
						lowercase    =			size
						lowercase    =			apply_ocr





		def 					UpperCAmelCase__ (self   :						List[str]					)       ->			int:
						return {"do_resize": self.do_resize, "size": self.size, "apply_ocr": self.apply_ocr}




@require_torch
@require_pytesseract
class    UpperCAmelCase			(    __A      ,							unittest.TestCase	):
		UpperCAmelCase       :						List[Any]			      =		LayoutLMvaImageProcessor if is_pytesseract_available() else None




		def 					UpperCAmelCase__ (self   :						List[Any]					)       ->			Optional[int]:
						lowercase    =			LayoutLMvaImageProcessingTester(self					)




		@property
		def 					UpperCAmelCase__ (self   :						Optional[Any]					)       ->			List[Any]:
						return self.image_processor_tester.prepare_image_processor_dict()




		def 					UpperCAmelCase__ (self   :						Tuple					)       ->			List[Any]:
						lowercase    =			self.image_processing_class(**self.image_processor_dict					)
						self.assertTrue(hasattr(UpperCamelCase__				,      "do_resize"					)					)
						self.assertTrue(hasattr(UpperCamelCase__				,      "size"					)					)
						self.assertTrue(hasattr(UpperCamelCase__				,      "apply_ocr"					)					)




		def 					UpperCAmelCase__ (self   :						Optional[Any]					)       ->			Optional[Any]:
						lowercase    =			self.image_processing_class.from_dict(self.image_processor_dict					)
						self.assertEqual(image_processor.size				,      {"height": 1_8, "width": 1_8}					)

						lowercase    =			self.image_processing_class.from_dict(self.image_processor_dict				,      size=4_2					)
						self.assertEqual(image_processor.size				,      {"height": 4_2, "width": 4_2}					)




		def 					UpperCAmelCase__ (self   :						List[Any]					)       ->			Tuple:
						pass




		def 					UpperCAmelCase__ (self   :						Optional[int]					)       ->			List[Any]:
						lowercase    =			self.image_processing_class(**self.image_processor_dict					)
						# create random PIL images
						lowercase    =			prepare_image_inputs(self.image_processor_tester				,      equal_resolution=UpperCamelCase__					)
						for image in image_inputs:
										self.assertIsInstance(UpperCamelCase__				,      Image.Image					)

						# Test not batched input
						lowercase    =			image_processing(image_inputs[0]				,      return_tensors="pt"					)
						self.assertEqual(
						    encoding.pixel_values.shape				,      (
						        1,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )

						self.assertIsInstance(encoding.words				,      UpperCamelCase__					)
						self.assertIsInstance(encoding.boxes				,      UpperCamelCase__					)

						# Test batched
						lowercase    =			image_processing(UpperCamelCase__				,      return_tensors="pt"					).pixel_values
						self.assertEqual(
						    encoded_images.shape				,      (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )




		def 					UpperCAmelCase__ (self   :						List[Any]					)       ->			Tuple:
						lowercase    =			self.image_processing_class(**self.image_processor_dict					)
						# create random numpy tensors
						lowercase    =			prepare_image_inputs(self.image_processor_tester				,      equal_resolution=UpperCamelCase__				,      numpify=UpperCamelCase__					)
						for image in image_inputs:
										self.assertIsInstance(UpperCamelCase__				,      np.ndarray					)

						# Test not batched input
						lowercase    =			image_processing(image_inputs[0]				,      return_tensors="pt"					).pixel_values
						self.assertEqual(
						    encoded_images.shape				,      (
						        1,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )

						# Test batched
						lowercase    =			image_processing(UpperCamelCase__				,      return_tensors="pt"					).pixel_values
						self.assertEqual(
						    encoded_images.shape				,      (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )




		def 					UpperCAmelCase__ (self   :						Union[str, Any]					)       ->			Dict:
						lowercase    =			self.image_processing_class(**self.image_processor_dict					)
						# create random PyTorch tensors
						lowercase    =			prepare_image_inputs(self.image_processor_tester				,      equal_resolution=UpperCamelCase__				,      torchify=UpperCamelCase__					)
						for image in image_inputs:
										self.assertIsInstance(UpperCamelCase__				,      torch.Tensor					)

						# Test not batched input
						lowercase    =			image_processing(image_inputs[0]				,      return_tensors="pt"					).pixel_values
						self.assertEqual(
						    encoded_images.shape				,      (
						        1,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )

						# Test batched
						lowercase    =			image_processing(UpperCamelCase__				,      return_tensors="pt"					).pixel_values
						self.assertEqual(
						    encoded_images.shape				,      (
						        self.image_processor_tester.batch_size,
						        self.image_processor_tester.num_channels,
						        self.image_processor_tester.size["height"],
						        self.image_processor_tester.size["width"],
						    )				,      )





		def 					UpperCAmelCase__ (self   :						Optional[Any]					)       ->			Dict:
						lowercase    =			LayoutLMvaImageProcessor()

						from datasets import load_dataset

						lowercase    =			load_dataset("hf-internal-testing/fixtures_docvqa"				,      split="test"					)

						lowercase    =			Image.open(ds[0]["file"]					).convert("RGB"					)

						lowercase    =			image_processing(UpperCamelCase__				,      return_tensors="pt"					)

						self.assertEqual(encoding.pixel_values.shape				,      (1, 3, 2_2_4, 2_2_4)					)
						self.assertEqual(len(encoding.words					)				,      len(encoding.boxes					)					)

						# fmt: off
						# the words and boxes were obtained with Tesseract 4.1.1
						lowercase    =			[["11:14", "to", "11:39", "a.m", "11:39", "to", "11:44", "a.m.", "11:44", "a.m.", "to", "12:25", "p.m.", "12:25", "to", "12:58", "p.m.", "12:58", "to", "4:00", "p.m.", "2:00", "to", "5:00", "p.m.", "Coffee", "Break", "Coffee", "will", "be", "served", "for", "men", "and", "women", "in", "the", "lobby", "adjacent", "to", "exhibit", "area.", "Please", "move", "into", "exhibit", "area.", "(Exhibits", "Open)", "TRRF", "GENERAL", "SESSION", "(PART", "|)", "Presiding:", "Lee", "A.", "Waller", "TRRF", "Vice", "President", "“Introductory", "Remarks”", "Lee", "A.", "Waller,", "TRRF", "Vice", "Presi-", "dent", "Individual", "Interviews", "with", "TRRF", "Public", "Board", "Members", "and", "Sci-", "entific", "Advisory", "Council", "Mem-", "bers", "Conducted", "by", "TRRF", "Treasurer", "Philip", "G.", "Kuehn", "to", "get", "answers", "which", "the", "public", "refrigerated", "warehousing", "industry", "is", "looking", "for.", "Plus", "questions", "from", "the", "floor.", "Dr.", "Emil", "M.", "Mrak,", "University", "of", "Cal-", "ifornia,", "Chairman,", "TRRF", "Board;", "Sam", "R.", "Cecil,", "University", "of", "Georgia", "College", "of", "Agriculture;", "Dr.", "Stanley", "Charm,", "Tufts", "University", "School", "of", "Medicine;", "Dr.", "Robert", "H.", "Cotton,", "ITT", "Continental", "Baking", "Company;", "Dr.", "Owen", "Fennema,", "University", "of", "Wis-", "consin;", "Dr.", "Robert", "E.", "Hardenburg,", "USDA.", "Questions", "and", "Answers", "Exhibits", "Open", "Capt.", "Jack", "Stoney", "Room", "TRRF", "Scientific", "Advisory", "Council", "Meeting", "Ballroom", "Foyer"]]  # noqa: E231
						lowercase    =			[[[1_4_1, 5_7, 2_1_4, 6_9], [2_2_8, 5_8, 2_5_2, 6_9], [1_4_1, 7_5, 2_1_6, 8_8], [2_3_0, 7_9, 2_8_0, 8_8], [1_4_2, 2_6_0, 2_1_8, 2_7_3], [2_3_0, 2_6_1, 2_5_5, 2_7_3], [1_4_3, 2_7_9, 2_1_8, 2_9_0], [2_3_1, 2_8_2, 2_9_0, 2_9_1], [1_4_3, 3_4_2, 2_1_8, 3_5_4], [2_3_1, 3_4_5, 2_8_9, 3_5_5], [2_0_2, 3_6_2, 2_2_7, 3_7_3], [1_4_3, 3_7_9, 2_2_0, 3_9_2], [2_3_1, 3_8_2, 2_9_1, 3_9_4], [1_4_4, 7_1_4, 2_2_0, 7_2_6], [2_3_1, 7_1_5, 2_5_6, 7_2_6], [1_4_4, 7_3_2, 2_2_0, 7_4_5], [2_3_2, 7_3_6, 2_9_1, 7_4_7], [1_4_4, 7_6_9, 2_1_8, 7_8_2], [2_3_1, 7_7_0, 2_5_6, 7_8_2], [1_4_1, 7_8_8, 2_0_2, 8_0_1], [2_1_5, 7_9_1, 2_7_4, 8_0_4], [1_4_3, 8_2_6, 2_0_4, 8_3_8], [2_1_5, 8_2_6, 2_4_0, 8_3_8], [1_4_2, 8_4_4, 2_0_2, 8_5_7], [2_1_5, 8_4_7, 2_7_4, 8_5_9], [3_3_4, 5_7, 4_2_7, 6_9], [4_4_0, 5_7, 5_2_2, 6_9], [3_6_9, 7_5, 4_6_1, 8_8], [4_6_9, 7_5, 5_1_6, 8_8], [5_2_8, 7_6, 5_6_2, 8_8], [5_7_0, 7_6, 6_6_7, 8_8], [6_7_5, 7_5, 7_1_1, 8_7], [7_2_1, 7_9, 7_7_8, 8_8], [7_8_9, 7_5, 8_4_0, 8_8], [3_6_9, 9_7, 4_7_0, 1_0_7], [4_8_4, 9_4, 5_0_7, 1_0_6], [5_1_8, 9_4, 5_6_2, 1_0_7], [5_7_6, 9_4, 6_5_5, 1_1_0], [6_6_8, 9_4, 7_9_2, 1_0_9], [8_0_4, 9_5, 8_2_9, 1_0_7], [3_6_9, 1_1_3, 4_6_5, 1_2_5], [4_7_7, 1_1_6, 5_4_7, 1_2_5], [5_6_2, 1_1_3, 6_5_8, 1_2_5], [6_7_1, 1_1_6, 7_4_8, 1_2_5], [7_6_1, 1_1_3, 8_1_1, 1_2_5], [3_6_9, 1_3_1, 4_6_5, 1_4_3], [4_7_7, 1_3_3, 5_4_8, 1_4_3], [5_6_3, 1_3_0, 6_9_8, 1_4_5], [7_1_0, 1_3_0, 8_0_2, 1_4_6], [3_3_6, 1_7_1, 4_1_2, 1_8_3], [4_2_3, 1_7_1, 5_7_2, 1_8_3], [5_8_2, 1_7_0, 7_1_6, 1_8_4], [7_2_8, 1_7_1, 8_1_7, 1_8_7], [8_2_9, 1_7_1, 8_4_4, 1_8_6], [3_3_8, 1_9_7, 4_8_2, 2_1_2], [5_0_7, 1_9_6, 5_5_7, 2_0_9], [5_6_9, 1_9_6, 5_9_5, 2_0_8], [6_1_0, 1_9_6, 7_0_2, 2_0_9], [5_0_5, 2_1_4, 5_8_3, 2_2_6], [5_9_5, 2_1_4, 6_5_6, 2_2_7], [6_7_0, 2_1_5, 8_0_7, 2_2_7], [3_3_5, 2_5_9, 5_4_3, 2_7_4], [5_5_6, 2_5_9, 7_0_8, 2_7_2], [3_7_2, 2_7_9, 4_2_2, 2_9_1], [4_3_5, 2_7_9, 4_6_0, 2_9_1], [4_7_4, 2_7_9, 5_7_4, 2_9_2], [5_8_7, 2_7_8, 6_6_4, 2_9_1], [6_7_6, 2_7_8, 7_3_8, 2_9_1], [7_5_1, 2_7_9, 8_3_4, 2_9_1], [3_7_2, 2_9_8, 4_3_4, 3_1_0], [3_3_5, 3_4_1, 4_8_3, 3_5_4], [4_9_7, 3_4_1, 6_5_5, 3_5_4], [6_6_7, 3_4_1, 7_2_8, 3_5_4], [7_4_0, 3_4_1, 8_2_5, 3_5_4], [3_3_5, 3_6_0, 4_3_0, 3_7_2], [4_4_2, 3_6_0, 5_3_4, 3_7_2], [5_4_5, 3_5_9, 6_8_7, 3_7_2], [6_9_7, 3_6_0, 7_5_4, 3_7_2], [7_6_5, 3_6_0, 8_2_3, 3_7_3], [3_3_4, 3_7_8, 4_2_8, 3_9_1], [4_4_0, 3_7_8, 5_7_7, 3_9_4], [5_9_0, 3_7_8, 7_0_5, 3_9_1], [7_2_0, 3_7_8, 8_0_1, 3_9_1], [3_3_4, 3_9_7, 4_0_0, 4_0_9], [3_7_0, 4_1_6, 5_2_9, 4_2_9], [5_4_4, 4_1_6, 5_7_6, 4_3_2], [5_8_7, 4_1_6, 6_6_5, 4_2_8], [6_7_7, 4_1_6, 8_1_4, 4_2_9], [3_7_2, 4_3_5, 4_5_2, 4_5_0], [4_6_5, 4_3_4, 4_9_5, 4_4_7], [5_1_1, 4_3_4, 6_0_0, 4_4_7], [6_1_1, 4_3_6, 6_3_7, 4_4_7], [6_4_9, 4_3_6, 6_9_4, 4_5_1], [7_0_5, 4_3_8, 8_2_4, 4_4_7], [3_6_9, 4_5_3, 4_5_2, 4_6_6], [4_6_4, 4_5_4, 5_0_9, 4_6_6], [5_2_2, 4_5_3, 6_1_1, 4_6_9], [6_2_5, 4_5_3, 7_9_2, 4_6_9], [3_7_0, 4_7_2, 5_5_6, 4_8_8], [5_7_0, 4_7_2, 6_8_4, 4_8_7], [6_9_7, 4_7_2, 7_1_8, 4_8_5], [7_3_2, 4_7_2, 8_3_5, 4_8_8], [3_6_9, 4_9_0, 4_1_1, 5_0_3], [4_2_5, 4_9_0, 4_8_4, 5_0_3], [4_9_6, 4_9_0, 6_3_5, 5_0_6], [6_4_5, 4_9_0, 7_0_7, 5_0_3], [7_1_8, 4_9_1, 7_6_1, 5_0_3], [7_7_1, 4_9_0, 8_4_0, 5_0_3], [3_3_6, 5_1_0, 3_7_4, 5_2_1], [3_8_8, 5_1_0, 4_4_7, 5_2_2], [4_6_0, 5_1_0, 4_8_9, 5_2_1], [5_0_3, 5_1_0, 5_8_0, 5_2_2], [5_9_2, 5_0_9, 7_3_6, 5_2_5], [7_4_5, 5_0_9, 7_7_0, 5_2_2], [7_8_1, 5_0_9, 8_4_0, 5_2_2], [3_3_8, 5_2_8, 4_3_4, 5_4_1], [4_4_8, 5_2_8, 5_9_6, 5_4_1], [6_0_9, 5_2_7, 6_8_7, 5_4_0], [7_0_0, 5_2_8, 7_9_2, 5_4_1], [3_3_6, 5_4_6, 3_9_7, 5_5_9], [4_0_7, 5_4_6, 4_3_1, 5_5_9], [4_4_3, 5_4_6, 5_2_5, 5_6_0], [5_3_7, 5_4_6, 6_8_0, 5_6_2], [6_8_8, 5_4_6, 7_1_4, 5_5_9], [7_2_2, 5_4_6, 8_3_7, 5_6_2], [3_3_6, 5_6_5, 4_4_9, 5_8_1], [4_6_1, 5_6_5, 4_8_5, 5_7_7], [4_9_7, 5_6_5, 6_6_5, 5_8_1], [6_8_1, 5_6_5, 7_1_8, 5_7_7], [7_3_2, 5_6_5, 8_3_7, 5_8_0], [3_3_7, 5_8_4, 4_3_8, 5_9_7], [4_5_2, 5_8_3, 5_2_1, 5_9_6], [5_3_5, 5_8_4, 6_7_7, 5_9_9], [6_9_0, 5_8_3, 7_8_7, 5_9_6], [8_0_1, 5_8_3, 8_2_5, 5_9_6], [3_3_8, 6_0_2, 4_7_8, 6_1_5], [4_9_2, 6_0_2, 5_3_0, 6_1_4], [5_4_3, 6_0_2, 6_3_8, 6_1_5], [6_5_0, 6_0_2, 6_7_6, 6_1_4], [6_8_8, 6_0_2, 7_8_8, 6_1_5], [8_0_2, 6_0_2, 8_4_3, 6_1_4], [3_3_7, 6_2_1, 5_0_2, 6_3_3], [5_1_6, 6_2_1, 6_1_5, 6_3_7], [6_2_9, 6_2_1, 7_7_4, 6_3_6], [7_8_9, 6_2_1, 8_2_7, 6_3_3], [3_3_7, 6_3_9, 4_1_8, 6_5_2], [4_3_2, 6_4_0, 5_7_1, 6_5_3], [5_8_7, 6_3_9, 7_3_1, 6_5_5], [7_4_3, 6_3_9, 7_6_9, 6_5_2], [7_8_0, 6_3_9, 8_4_1, 6_5_2], [3_3_8, 6_5_8, 4_4_0, 6_7_3], [4_5_5, 6_5_8, 4_9_1, 6_7_0], [5_0_8, 6_5_8, 6_0_2, 6_7_1], [6_1_6, 6_5_8, 6_3_8, 6_7_0], [6_5_4, 6_5_8, 8_3_5, 6_7_4], [3_3_7, 6_7_7, 4_2_9, 6_8_9], [3_3_7, 7_1_4, 4_8_2, 7_2_6], [4_9_5, 7_1_4, 5_4_8, 7_2_6], [5_6_1, 7_1_4, 6_8_3, 7_2_6], [3_3_8, 7_7_0, 4_6_1, 7_8_2], [4_7_4, 7_6_9, 5_5_4, 7_8_5], [4_8_9, 7_8_8, 5_6_2, 8_0_3], [5_7_6, 7_8_8, 6_4_3, 8_0_1], [6_5_6, 7_8_7, 7_5_1, 8_0_4], [7_6_4, 7_8_8, 8_4_4, 8_0_1], [3_3_4, 8_2_5, 4_2_1, 8_3_8], [4_3_0, 8_2_4, 5_7_4, 8_3_8], [5_8_4, 8_2_4, 7_2_3, 8_4_1], [3_3_5, 8_4_4, 4_5_0, 8_5_7], [4_6_4, 8_4_3, 5_8_3, 8_6_0], [6_2_8, 8_6_2, 7_5_5, 8_7_5], [7_6_9, 8_6_1, 8_4_8, 8_7_8]]]  # noqa: E231
						# fmt: on

						self.assertListEqual(encoding.words				,      UpperCamelCase__					)
						self.assertListEqual(encoding.boxes				,      UpperCamelCase__					)

						# with apply_OCR = False
						lowercase    =			LayoutLMvaImageProcessor(apply_ocr=UpperCamelCase__					)

						lowercase    =			image_processing(UpperCamelCase__				,      return_tensors="pt"					)

						self.assertEqual(encoding.pixel_values.shape				,      (1, 3, 2_2_4, 2_2_4)					)












'''simple docstring'''







import os
import sys
import unittest


__lowerCAmelCase        =							os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


__lowerCAmelCase        =							os.path.join("tests", "models", "bert", "test_modeling_bert.py")
__lowerCAmelCase        =							os.path.join("tests", "models", "blip", "test_modeling_blip.py")




class   __SCREAMING_SNAKE_CASE       (unittest.TestCase       ):


  """simple docstring"""


  def    _a       (			self	):






         """simple docstring"""


         a_						     =			get_test_to_tester_mapping(UpperCamelCase__	)
         a_						     =			get_test_to_tester_mapping(UpperCamelCase__	)

         a_						     =			{'BertModelTest': 'BertModelTester'}

         a_						     =			{
             'BlipModelTest': 'BlipModelTester',
             'BlipTextImageModelTest': 'BlipTextImageModelsModelTester',
             'BlipTextModelTest': 'BlipTextModelTester',
             'BlipTextRetrievalModelTest': 'BlipTextRetrievalModelTester',
             'BlipVQAModelTest': 'BlipVQAModelTester',
             'BlipVisionModelTest': 'BlipVisionModelTester',
         }

         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)
         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)







  def    _a       (			self	):






         """simple docstring"""


         a_						     =			get_model_to_test_mapping(UpperCamelCase__	)
         a_						     =			get_model_to_test_mapping(UpperCamelCase__	)

         a_						     =			{
             'BertForMaskedLM': ['BertModelTest'],
             'BertForMultipleChoice': ['BertModelTest'],
             'BertForNextSentencePrediction': ['BertModelTest'],
             'BertForPreTraining': ['BertModelTest'],
             'BertForQuestionAnswering': ['BertModelTest'],
             'BertForSequenceClassification': ['BertModelTest'],
             'BertForTokenClassification': ['BertModelTest'],
             'BertLMHeadModel': ['BertModelTest'],
             'BertModel': ['BertModelTest'],
         }

         a_						     =			{
             'BlipForConditionalGeneration': ['BlipTextImageModelTest'],
             'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTest'],
             'BlipForQuestionAnswering': ['BlipVQAModelTest'],
             'BlipModel': ['BlipModelTest'],
             'BlipTextModel': ['BlipTextModelTest'],
             'BlipVisionModel': ['BlipVisionModelTest'],
         }

         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)
         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)







  def    _a       (			self	):






         """simple docstring"""


         a_						     =			get_model_to_tester_mapping(UpperCamelCase__	)
         a_						     =			get_model_to_tester_mapping(UpperCamelCase__	)

         a_						     =			{
             'BertForMaskedLM': ['BertModelTester'],
             'BertForMultipleChoice': ['BertModelTester'],
             'BertForNextSentencePrediction': ['BertModelTester'],
             'BertForPreTraining': ['BertModelTester'],
             'BertForQuestionAnswering': ['BertModelTester'],
             'BertForSequenceClassification': ['BertModelTester'],
             'BertForTokenClassification': ['BertModelTester'],
             'BertLMHeadModel': ['BertModelTester'],
             'BertModel': ['BertModelTester'],
         }

         a_						     =			{
             'BlipForConditionalGeneration': ['BlipTextImageModelsModelTester'],
             'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTester'],
             'BlipForQuestionAnswering': ['BlipVQAModelTester'],
             'BlipModel': ['BlipModelTester'],
             'BlipTextModel': ['BlipTextModelTester'],
             'BlipVisionModel': ['BlipVisionModelTester'],
         }

         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)
         self.assertEqual(get_test_info.to_json(UpperCamelCase__	)   ,	UpperCamelCase__	)




